docstr: :param term_doc_matrix: TermDocMatrix
  :param axes: pd.DataFrame
  :param x_axis_name: str
  :param y_axis_name: str
  :param labels: dict, optional
  :param distance_measure: DistanceMeasureBase, EuclideanDistance by default
docstr_tok: [":","param","term_doc_matrix",":","TermDocMatrix",":","param","axes",":","pd.DataFrame",":","param","x_axis_name",":","str",":","param","y_axis_name",":","str",":","param","labels",":","dict",",","optional",":","param","distance_measure",":","DistanceMeasureBase",",","EuclideanDistance","by","default"]
code: def __init__(
      self,
      term_doc_matrix,
      axes,
      x_axis_name,
      y_axis_name,
      labels=None,
      distance_measure=EuclideanDistance,
  ):
      """
  
      :param term_doc_matrix: TermDocMatrix
      :param axes: pd.DataFrame
      :param x_axis_name: str
      :param y_axis_name: str
      :param labels: dict, optional
      :param distance_measure: DistanceMeasureBase, EuclideanDistance by default
      """
      self.term_doc_matrix = term_doc_matrix
      assert type(axes) == pd.DataFrame
      assert set(axes.columns) == set(["x", "y"])
      assert set(axes.index) == set(term_doc_matrix.get_terms())
      self.axes = axes
      self.y_axis_name = y_axis_name
      self.x_axis_name = x_axis_name
      if labels is None:
          self._labels = {}
      else:
          self._labels = labels
      self._distance_measure = distance_measure
  
file_path: scattertext/scattertext/semioticsquare/SemioticSquareFromAxes.py
imports: import numpy
  import pandas
  from scattertext.distancemeasures.EuclideanDistance import EuclideanDistance
  from scattertext.semioticsquare.SemioticSquare import SemioticSquareBase
label_desc: Use image node_id 1 to create a new SemioticSquareFromAxes object from inherited base classes: SemioticSquareBase with example: obj = SemioticSquareFromAxes(term_doc_matrix, axes, x_axis_name, y_axis_name, labels, distance_measure)